Evaluation of a "Smart" Pedestrian Counting System Based on Echo State Networks

Mathews, Emi; Poigné, Axel

doi:10.1155/2009/352172

Cited by 11 publications

(5 citation statements)

References 8 publications

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“…Mathews and Poigné [13] introduced a system based on a set of passive infrared beacons. The detection of people is done with an Echo State Network which is trained with a set of motion patterns obtained with a simulator.…”

Section: Range Laser Methodsmentioning

confidence: 99%

People counting with re-identification using depth cameras

Hernández¹,

Castrillón²,

Lorenzo³

2011

4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011)

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Low cost real-time depth cameras offer new sensors for a wide field of applications apart from the gaming world. Other active research scenarios as for example surveillance, can take advantage of the capabilities offered by this kind of sensors that integrate depth and visual information.In this paper, we present a system that operates in a novel application context for these devices, in troublesome scenarios where illumination conditions can suffer sudden changes. We focus on the people counting problem with re-identification and trajectory analysis.Automatic people counting offers different application contexts related to security, safety, energy saving or fraud control. Here we go one step further and give hints to extract useful information using depth cameras. The processing of that information allows us to analyze the individuals behavior, particularly if they go away from the typical trajectory, and the problem of re-identifying people.

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Section: Range Laser Methodsmentioning

confidence: 99%

People counting with re-identification using depth cameras

Hernández¹,

Castrillón²,

Lorenzo³

2011

4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011)

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“…Mathews and Poigné [8] introduced a system based on a set of passive infrared beacons. The detection of people is done with an Echo State Network which is trained with a set of motion patterns obtained with a simulator.…”

Section: Range Laser Methodsmentioning

confidence: 99%

Multi-sensor People Counting

Hernández-Sosa

Castrillón-Santana

Lorenzo-Navarro

2011

Pattern Recognition and Image Analysis

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Abstract. An accurate estimation of the number of people entering / leaving a controlled area is an interesting capability for automatic surveillance systems. Potential applications where this technology can be applied include those related to security, safety, energy saving or fraud control. In this paper we present a novel configuration of a multi-sensor system combining both visual and range data specially suited for troublesome scenarios such as public transportation. The approach applies probabilistic estimation filters on raw sensor data to create intermediate level hypothesis that are later fused using a certainty-based integration stage. Promising results have been obtained in several tests performed on a realistic test bed scenario under variable lightning conditions.

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“…Spatio-temporal data widely appear in traffic application. In this domain, ESNs can be used in traffic forecasting [258,259,47,258], destination prediction [260], bike-sharing application [261,111] and pedestrian counting system [262].…”

Section: Real-world Tasks Orientatedmentioning

confidence: 99%

A Review of Designs and Applications of Echo State Networks

Sun¹,

Song²,

Hong³

et al. 2020

Preprint

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Recurrent Neural Networks (RNNs) have demonstrated their outstanding ability in sequence tasks and have achieved state-of-the-art in wide range of applications, such as industrial, medical, economic and linguistic. Echo State Network (ESN) is simple type of RNNs and has emerged in the last decade as an alternative to gradient descent training based RNNs. ESN, with a strong theoretical ground, is practical, conceptually simple, easy to implement. It avoids non-converging and computationally expensive in the gradient descent methods. Since ESN was put forward in 2002, abundant existing works have promoted the progress of ESN, and the recently introduced Deep ESN model opened the way to uniting the merits of deep learning and ESNs. Besides, the combinations of ESNs with other machine learning models have also overperformed baselines in some applications. However, the apparent simplicity of ESNs can sometimes be deceptive and successfully applying ESNs needs some experience. Thus, in this paper, we categorize the ESN-based methods to basic ESNs, DeepESNs and combinations, then analyze them from the perspective of theoretical studies, network designs and specific applications. Finally, we discuss the challenges and opportunities of ESNs by summarizing the open questions and proposing possible future works.

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Evaluation of a "Smart" Pedestrian Counting System Based on Echo State Networks

Cited by 11 publications

References 8 publications

People counting with re-identification using depth cameras

People counting with re-identification using depth cameras

Multi-sensor People Counting

A Review of Designs and Applications of Echo State Networks

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